class_docstr: GRU gate for matrix, similar to the official code.
  Please refer to section 3.4 of the paper for the formula.
code: def forward(self, x, hidden):
      out = self.activation(
          self.W.matmul(x) + self.U.matmul(hidden) + self.bias
      )
  
      return out
  
imports: import torch
  import torch.nn
  from dgl.nn.pytorch import GraphConv
  from torch.nn import init
  from torch.nn.parameter import Parameter
label_desc: Use image node_id 3 for calling the MatGRUGate obj's underlying member method code with example usage: obj.forward(x, hidden) and returns: out